Package tv.floe.metronome.deeplearning.neuralnetwork.gradient

Examples of tv.floe.metronome.deeplearning.neuralnetwork.gradient.NeuralNetworkGradient

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      this.trainingDataset = input;
     
    }
   
    // actually performs CDk
    NeuralNetworkGradient gradient = getGradient(new Object[]{k,learningRate});
   
    //W.addi(gradient.getwGradient());
    this.connectionWeights = this.connectionWeights.plus(gradient.getwGradient());
   
    //hBias.addi(gradient.gethBiasGradient());
    this.hiddenBiasNeurons = this.hiddenBiasNeurons.plus(gradient.gethBiasGradient());
   
    //vBias.addi(gradient.getvBiasGradient());
    this.visibleBiasNeurons = this.visibleBiasNeurons.plus( gradient.getvBiasGradient() );
   

  }
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    //this.hiddenBiasNeurons = this.hiddenBiasNeurons.plus( hBiasAdd );   

    return new NeuralNetworkGradient(wGradient, vBiasGradient, hBiasGradient);
   
   
  }
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         this.k = 15;
   
    k = this.k;

    // this is where the RBM actually performs CDk
    NeuralNetworkGradient gradient = network.getGradient( new Object[]{ k, lr } );
   
    Matrix wAdd = gradient.getwGradient();
    Matrix vBiasAdd = gradient.getvBiasGradient();
    Matrix hBiasAdd = gradient.gethBiasGradient();
   
    int idx = 0;
    for (int i = 0; i < MatrixUtils.length( wAdd ); i++) {
   
      buffer[idx++] = MatrixUtils.getElement( wAdd, i );
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Related Classes of tv.floe.metronome.deeplearning.neuralnetwork.gradient.NeuralNetworkGradient

  • tv.floe.metronome.deeplearning.rbm.RestrictedBoltzmannMachine
  • tv.floe.metronome.deeplearning.rbm.RestrictedBoltzmannMachineOptimizer
  • java.io.DataInput
  • java.io.DataOutputStream
  • java.io.DataOutput
  • java.io.DataInputStream
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